This disclosure relates generally to fraud detection, and more particularly to a system and method for abstracting transactions for visualization of fraud detection.
Conventional fraud detection systems usually give a score on a transaction of a Payment Card or Payment Instrument, such as an authorization for a credit or debit card. The score, representing a fraud risk level, is typically generated by an artificial intelligence system, such as a neural network trained on historical data. In most scenarios, a fraud case is created when the transaction score is above a fraud risk threshold. This score is usually used as the main criteria for creating cases, though expert rules can also create cases independent of the score. Some fraud detection systems provide reason codes for high score cases.
During case processing, an analyst attempts to contact the legitimate cardholder, often by phone, to review the transactions in question, to determine whether the account is in a fraudulent state. Sometimes the cardholder cannot be reached. Other times, the analyst may choose to not contact card holders for some types of cases to save time. In both of these situations, analysts may review the case and decide whether an account appears to be fraud based on their own intuition, or using their expert knowledge. Visualization techniques provide domain-specific interfaces that can help analysts make better decisions more quickly and easily.
Visualization is any technique for creating images, diagrams, or animations to present information in an intuitive way to users. Visualization translates data into a visible form that highlights important features of the data. It helps users to perceive important aspects of their data quickly by using innovative techniques and visual representations. Visualization provides different views to look at transaction data, and presents the data in intuitive, understandable, and actionable ways. Moreover, visualization can provide a highly interactive interface between human and automatic systems.
What is needed is visualization for a fraud detection system to provide abstraction for a transaction, a transaction history, transaction profiles, cardholder master-file, and fraud information.